DECISION SUPPORT FOR FOREIGN EXCHANGE USING NEURAL NETWORK AND BOLLINGER BAND

• Main Authors: Ting-Yu Lu, 盧廷宇
• Other Authors: Patrick S. Chen
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/12073850276221959655

碩士 === 大同大學 === 資訊經營學系(所) === 100 === Foreign exchange market in recent years become increasingly difficult to grasp, and investor mind with the the economic news announce becomes easy to lose control, the purpose of this study: By building in on propagation neural network combined with Bollinger Bands indicator and the RSI (Relative Strength Index) to design for the success of automated trading strategies, when the foreign exchange becomes difficult to predict, the automated trading system can help investor to avoid a significant loss of foreign exchange market, the tools used in this study as follows: MT4 trading platform;MQL4 language; implemented on euro /us dollar ;two traditional Forex indicators: Bollinger Bands and RSI indicators; and Fann (Fast based Artificial Neural network library) library to create the propagation neural network in the MT4 platform, which aims to borrow neural reached the automated trading capabilities.